Advanced Multispectral Computed Tomography (CT) Algorithms
Explosives represent a continuing threat to aviation security, leading to the ongoing need to robustly scan and screen for hazardous materials. In such security applications, many different materials may be scanned, and objects may appear in varying degrees of clutter. Image noise and metal artifacts are often severe and can lower the accuracy of material identification.
In this work, we focus on the development of advanced algorithms for robust extraction of the energy dependent properties of materials using X-ray illumination and different sensor configurations. Our algorithms will lead to the suppression of noise and artifacts in the resulting imagery, enabling improvements in the probability of detection and reducing false alarm rates in explosive detection applications.
Our approaches will increase the probability of detection as well as reduce the number of false alarms, which in turn can reduce the need for On Screen Anomaly Resolution Protocol (OSARP) and manual inspection.Year 4 Annual Report
W. Clem Karl
Faculty and Staff Currently Involved in Project
Students Currently Involved in Project
- Parisa Babahedarian
- Usman Ghani
- Trent Montgomery